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I am writting a c++ program in which I define a function $$\displaystyle F(t) = \sum_{i}r_i\,H(t-t_i)$$ where $H$ is the heaviside function, $t_i$ are optimal parameters which are mutable.

The program is derived by automatic differentiation using ADOL-C. I am wondering whether I should be careful when I am implementing the function $f$ regarding branching and looping.

I would create the function:

template <class Tdouble> Tdouble myfunF ( Tdouble t, Tdouble *tis, int nbti)
{
  Tdouble res = 0.; 
  double ri = 0.; 
  for(int id=0;i<nbti;++i)
  {
    ri = ...;  
    if (t>ti){ 
      res = res + ri; 
    }   
  }
  return res ;
}

The Tdouble type is similar to the adouble type in ADOL-C. How to analyze if this construction is suitable for automatic differentiation using ADOL-C and rewrite the code ?

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    $\begingroup$ yikesabee. Does any automatic differentiation package handle distributional derivatives correctly? (Only useful under an integral, right?) IIRC, Griewank only discusses non-differentiable functions like abs. $\endgroup$
    – user14717
    May 23, 2019 at 19:06

1 Answer 1

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I used "condassign(a,b,c,d)" for branching in ADOL-C

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